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    <text style="display:block; font-size:42px; font-weight:800; color:#2c3e50; margin:20px 0; text-shadow:2px 2px 4px rgba(0,0,0,0.1);">深度学习在医学影像分析中的应用</text>
    <text style="display:block; font-size:20px; color:#34495e; letter-spacing:1px;">作者：王小明，陈晓华，李建国</text>
    <text style="display:block; font-size:18px; color:#7f8c8d; margin-top:8px;">单位：清华大学人工智能研究院</text>
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        <div class="abstract" style="background:linear-gradient(145deg,#f8f9fa,#e9ecef); padding:20px; border-radius:8px; box-shadow:0 4px 6px rgba(0,0,0,0.05);">
            <text style="display:block; font-size:28px; font-weight:700; color:#2980b9; margin-bottom:15px;">◆ 研究摘要</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50;">本研究提出新型卷积神经网络架构MedNet3D，通过三维特征提取模块实现多模态医学影像的精准分析...</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50; margin-top:12px;">在10个公开数据集上的实验表明，本方法在分割精度上提升12.7%，推理速度加快40%...</text>
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        <div class="introduction" style="background:#edf2f7; padding:20px; grid-column:1/-1; border-radius:8px;">
            <text style="display:block; font-size:28px; font-weight:700; color:#27ae60; margin-bottom:15px;">◆ 研究背景</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50;">随着医学影像数据量指数级增长，传统分析方法面临效率瓶颈...</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50; margin-top:10px;">现有深度学习模型在三维医学影像处理中存在参数量大、计算效率低等问题...</text>
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        <div class="method" style="background:#fff5e6; padding:20px; border-left:6px solid #f39c12; border-radius:0 8px 8px 0;">
            <text style="display:block; font-size:28px; font-weight:700; color:#d35400; margin-bottom:15px;">◆ 技术路线</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50;">1. 三维可分离卷积模块设计</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50;">2. 多尺度特征融合机制</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50;">3. 轻量化注意力模块集成</text>
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                <image style="width:100%; height:180px; border-radius:6px; box-shadow:0 3px 6px rgba(0,0,0,0.1);"></image>
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        <div class="experiment" style="background:#f9ebf2; padding:20px; border-left:6px solid #c0392b; border-radius:0 8px 8px 0;">
            <text style="display:block; font-size:28px; font-weight:700; color:#c0392b; margin-bottom:15px;">◆ 实验结果</text>
            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50;">在BraTS2022数据集上的对比实验结果：</text>
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                <image style="width:100%; height:140px; border:2px solid #e74c3c;"></image>
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            <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50; margin-top:15px;">消融实验表明各模块均带来显著性能提升...</text>
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    <div class="result" style="background:#e8f8f5; padding:25px; grid-column:1/-1; border-radius:8px; box-shadow:0 -4px 6px rgba(0,0,0,0.05);">
        <text style="display:block; font-size:28px; font-weight:700; color:#16a085; margin-bottom:15px;">◆ 研究结论</text>
        <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50;">提出的MedNet3D在保持计算效率的同时显著提升分割精度...</text>
        <text style="display:block; font-size:17px; line-height:1.8; color:#2c3e50; margin-top:10px;">未来工作将探索模型在移动医疗设备上的部署应用...</text>
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